The extraction of three-dimensional images from volume data consisting of a stack of two-dimensional images is attracting significant attention in light of the general recognition of the likely impact that computer integrated surgical systems and technology will have in the future.
Computer assisted surgical planning and computer assisted surgical execution systems accurately perform optimised patient specific treatment plans. The input data to these types of systems are volume data usually obtained from tomographic imaging techniques. The objects and structures embedded in the volume data represent physical structures. In many instances, the medical practitioner is required to feel the patient in the diagnosis process.
An example where systems are used for the extraction and editing of three-dimensional objects from volume images is interventional angiography which has generated significant research and development on the three-dimensional reconstruction of arterial vessels from planar radiology obtained at several angles around the subject. In order to obtain a three-dimensional reconstruction from a C-arm mounted XRII traditionally the trajectory of the source and detectors system is characterized and the pixel size is computed. Various methods have been proposed in the past to compute different sets of characterization parameters.
Different approaches have also been proposed for vascular shape segmentation and structure extraction using mathematical morphology, region growing schemes and shape features in addition to greyscale information. In one particular method to extract a three-dimensional structure of blood vessels in the lung region from chest X-ray CT images, the proposal includes a recursive search method of the cross section of tree structure objects. The reconstruction of a three-dimensional volume of the vessel structure has been demonstrated in less than 10 minutes after the acquisition of a rotational image. In this particular instance, the volume rendered three-dimensional image offers high quality views compared with results of other three-dimensional imaging modalities when applied to high contrast vessel data.
In previous studies, an interactive vessel tracing method has been used to obtain a cerebral model. As volume data sets often lack the resolution to allow automatic network segmentation for blood vessels, this approach provides a free-form curve drawing technique by which human perception is quantitatively passed to the computer, using a “reach-in” environment as provided by a “Virtual Workbench”. The “Virtual Workbench” is a virtual reality workstation that provides three-dimensional viewing by use of stereoscopic glasses and time split displays rendered using a computer graphics workstation.
This precise and dexterous environment transforms perception to allow the relatively easy identification of vessels. The tools exploit the reach-in hand-immersion abilities of the Virtual Workbench and allow sustained productive work and the generation of three dimensional texture sub-volumes to allow interactive vessel tracing in real-time. A set of magnetic resonance angiograph (MRA) data of the human brain is used for this purpose and a total of 251 segments of the cerebral vessels have been identified and registered based on the connection with the primary vasculature of the Visible Human male Data (VHD). The VHD represents the effort of the National Institute of Health in the United States to produce a complete, anatomically detailed three-dimensional representation of normal male, and female bodies.
Generally, the traditional Human Computer Interaction (HCI) methodology is considered to be cumbersome. For many intricate or complex functions there are too many buttons to be depressed on the keyboard mouse or other interfacing devices. These interfaces are not natural for human interaction particularly in the field of medical applications: since surgeons do not have the ability to use their hands to operate a computer and often communicate with their assistants even in the process of changing tools.
For many applications there is a need for an improved human machine interface that is better suited to the needs of humans and in particular for tasks such at those performed by surgeons.
The above discussion of documents, acts, materials, devices, articles or the like is included in this specification; solely for the purpose of providing a context for the present invention. It is not suggested or represented that any or all of these matters formed part of the prior art base or were common general knowledge in the field relevant to the present invention as it existed before the priority date of each claim of this application.